Data Science Lead

500M+ downloads. 80M+ monthly users. A decade of building – and we’re still accelerating. Flo is the world’s #1 health & fitness app worldwide on a mission to build a better future for female health. Backed by a $200M investment led by General Atlantic, we became the first product of our kind to reach a $1B valuation in 2024 – and we’re not slowing down. With 7M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust at scale. Now, we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better. The jobWe’re hiring a Data Science Lead in London to build and lead our Predictive Growth Optimisation team – pioneering ML models that power our user acquisition strategy, predict lifetime value, and optimise our $25M+ annual marketing spend across channels. This role owns the strategy, development, and continuous improvement of Flo’s pLTV system - a mission-critical model reused across UA, AdTech, personalisation, and financial forecasting. That is the core of the role. Alongside it, you'll stand up a Marketing Mix Modeling (MMM) capability to measure cross-channel effectiveness and inform budget allocation, and develop the algorithms to drive real-time UA campaign management. You'll lead a team building production systems that directly impact our growth trajectory, staying as hands-on as you choose. What you’ll do Lead & develop a team of 6+ ML and Backend engineers - hiring, mentoring, and setting technical direction Own pLTV strategy - architect and evolve our core predictive lifetime value models that inform millions in UA decisions Stand up MMM - build our Marketing Mix Modeling capability: adstock and saturation modelling, channel contribution, and budget allocation, calibrated against our incrementality experiments Power real-time campaign management - develop the algorithms that optimise our UA campaigns across channels in real time Build production ML systems - from real-time prediction services handling millions of daily predictions to MMM models Drive cross-functional impact - partner with Growth, Product, and Finance to translate business problems into ML solutions Shape technical architecture - guide MLOps infrastructure, monitoring, and rapid iteration cycles Stay as hands-on as you choose - modeling, architecture decisions, technical problem-solving; your call how deep you go. What you bring Technical Leadership 7+ years applied ML experience building and deploying models in production 4+ years managing technical teams (ML engineers, data scientists, or similar) Expert knowledge of ML fundamentals: supervised/unsupervised learning, time series; strong grounding in causal inference Experience with modern ML frameworks (TensorFlow, scikit-learn, CatBoost) Growth & Product Experience Experience with growth analytics, attribution modeling, or marketing effectiveness Understanding of use...